{"id":"W4416332606","doi":"10.1145/3777461","title":"Blockchain Meets Securities: A Scalable Tokenization Framework","year":2025,"lang":"en","type":"article","venue":"Distributed Ledger Technologies Research and Practice","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Lexical analysis; Market liquidity; Scalability; Asset (computer security); Smart contract; Voting; Shareholder","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00201024,0.0001887302,0.0002283703,0.0006399764,0.0009355149,0.0004179236,0.001716624,0.0006449447,0.000008880229],"category_scores_gemma":[0.0121723,0.0001817727,0.00003444363,0.004632202,0.0008695037,0.0003854118,0.001298771,0.001465071,0.0000296774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001162493,"about_ca_system_score_gemma":0.000173214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004880107,"about_ca_topic_score_gemma":0.000008524605,"domain_scores_codex":[0.9976308,0.0002817932,0.000301267,0.0007208075,0.0003805826,0.0006847451],"domain_scores_gemma":[0.994322,0.003262635,0.00009343567,0.001375213,0.0008835584,0.0000631732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002804297,0.0002147397,0.0001710323,0.00004233177,0.00004540431,0.00001648436,0.0001638563,0.000004229687,0.0002311563,0.9314546,0.01244155,0.0551866],"study_design_scores_gemma":[0.000285582,0.000136683,0.0001220891,0.0000963754,0.00001088586,0.00004341985,0.003414959,0.006176767,0.01044374,0.5623249,0.4167198,0.0002248321],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005562526,0.009241431,0.8244407,0.1506316,0.0001220414,0.0006966963,0.00004721955,0.002696473,0.006561284],"genre_scores_gemma":[0.9515284,0.002162072,0.0453748,0.0002530681,0.00001535418,0.0003912516,0.00002455747,0.000008964199,0.000241554],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9459658,"threshold_uncertainty_score":0.9961486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03060166717038328,"score_gpt":0.3578237952424816,"score_spread":0.3272221280720984,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}